{"id":"W2748472236","doi":"10.1039/c7lc00751e","title":"Reply to the ‘Comment on “Towards a personalized approach to aromatase inhibitor therapy: a digital microfluidic platform for rapid analysis of estradiol in core-needle-biopsies”’ by P. E. Lønning, <i>Lab Chip</i>, 2017, <b>17</b>, DOI: 10.1039/C7LC00617A","year":2017,"lang":"en","type":"letter","venue":"Lab on a Chip","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Lunenfeld-Tanenbaum Research Institute; Toronto Public Health; Mount Sinai Hospital","funders":"","keywords":"Aromatase inhibitor; Aromatase; Letrozole; Core (optical fiber); Lab-on-a-chip; Microfluidics; Medicine; Internal medicine; Computer science; Computational biology; Nanotechnology; Medical physics; Pharmacology; Biology; Materials science; Breast cancer; Telecommunications; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003267496,0.0006554998,0.0008359794,0.0002994116,0.0002318844,0.0001491589,0.0009972601,0.0005754278,0.00001349305],"category_scores_gemma":[0.0001198195,0.0004901505,0.0005842847,0.0003775581,0.0001785449,0.000009799514,0.0001981783,0.0005566235,0.00001005973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009730038,"about_ca_system_score_gemma":0.00009836473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001282845,"about_ca_topic_score_gemma":0.000004549415,"domain_scores_codex":[0.9972108,0.0000443273,0.0006076624,0.001181337,0.0003673466,0.0005885141],"domain_scores_gemma":[0.9971852,0.00006952149,0.000499192,0.001992728,0.0001117886,0.0001415535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007950282,0.0002991499,0.00001188848,0.00003873706,0.0004597724,0.000005629059,0.0001386282,0.00001340266,0.0424878,0.00002465092,0.9534674,0.002257863],"study_design_scores_gemma":[0.0009896798,0.001055193,0.00004070183,0.0001143071,0.0001569715,0.00001104358,0.00003590507,0.00007008851,0.05655317,0.00005042883,0.9403657,0.0005568602],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.2704489,0.004523381,0.008217928,0.6515474,0.000406663,0.01563842,0.04107374,0.0003120279,0.007831514],"genre_scores_gemma":[0.08880505,0.0009440422,0.007461502,0.8423564,0.002512427,0.002844537,0.04463589,0.0003566799,0.01008346],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.190809,"threshold_uncertainty_score":0.999755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03434480690896418,"score_gpt":0.288658919960104,"score_spread":0.2543141130511398,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}